1. Field of the Invention
This invention relates to devices for use in video applications, and particularly, to video signal filters.
2. Discussion of the Related Art
In video applications, it is often desirable to change the contrast and luminance associated with an imaged picture because, due to increased variations in the brilliance of the picture relative to the sensitivity of the means provided for acquiring or storing it, details in highly brilliant or very dark areas of the picture may fail to be adequately brought out.
It should not be overlooked that contrast is related to the details of an image, while luminance contains brilliance information associated with the image itself.
To modify the contrast and luminance associated with an image, and accordingly to solve this problem, two main approaches can be followed which are both known from literature.
In the first approach, the image is defined as the product of an illumination component i(y,x) from the light impinging on a picture being imaged and a reflectance component r(y,x) from the light being reflected by objects within said picture. Namely: EQU f(y,x)=i(y,x) r(y,x)
where, f(y,x) is the image to be processed, identified as a function of two variables, y and x, that represent the spatial co-ordinates of each of the picture elements or pixels that make up the image.
In the above definition of an image, the illumination component i(y,x) is responsible for most of the change in brilliance, while the reflectance component contains detail information.
The illumination component i(y,x), being tied to the image brilliance, represents the luminance in the above definition of an image, while the reflectance component, being tied to the image details, represents the contrast. Thus, the luminance and contrast associated with an image can be modified by acting on the components i(y,x) and r(y,x).
The aim is to reduce the illumination component i(y,x) and amplify the reflectance component r(y,x). To accomplish this aim, linear filters are employed which are usually of the high-pass type and operate in the density domain.
It should be considered that illumination i(y,x) varies slowly in space, and therefore, contains mostly low spatial frequencies present in an image, whereas reflectance, being a process of the high-pass type, mostly contains high spatial frequencies.
In order to work with linear filters of the high-pass type, a logarithmic transform of the illumination and reflectance components is used so that the filtering operation can be made linear, that is, EQU f'(y,x)=log[f(y,x)]=i'(y,x)+r'(y,x),
where i'(y,x)=log[i(y,x)] and r'(y,x)=log[r(y,x)]. The kind of filtering to which the illumination and reflectance components are subjected is called homomorphic.
The homomorphic filtering concept as applied to bi-dimensional images, and embodiments of linear filters of the high-pass type, are described by H. J. Kaufmann and M. A. Sid-Ahmed in the article, "Hardware Realization of a 2-D IIR Semisystolic Filter with Application to Real-Time Homomorphic Filtering", IEEE Transactions on Circuits and Systems for Video Technology, Vol. 3, No. 1, February 1993.
After filtering, to obtain the processed image, the reverse from the logarithmic transform should be carried out.
A disadvantage of using homomorphic filtering comes from the difficulty in setting a filter mask used to modify the contrast and luminance of an image. That setting is made specially difficult because the frequency characteristics of an image to be processed are not known "a priori". Known from the pertinent literature are ways of setting said mask which are based on:
a) a trial-and-error procedure for the frequency response of a filter;
b) a statistical model for the illumination and reflectance processes and attendant construction of a Wiener filter.
The second approach followed to modify the luminance and contrast associated with an image is based on the consideration that contrast may be obtained as the difference between the image itself and the mean value of the illumination component.
The mean value that the illumination component exhibits locally in an image is tied to the variation in the brilliance of said image, and, hence, to the luminance thereof.
Thus, by acting on the mean value of the illumination component, the luminance associated with an image can be modified.
An image to be treated is processed through a two-channel filter wherein one channel is reserved for processing the mean value of the illumination component, which represents the low spatial frequency component of said image, and the other channel is reserved for processing the contrast, which represents the high spatial frequency component.
Specifically, the two-channel filter acts, through non-linear characteristics, on grey levels of pixels associated with the image being processed which represent the low and high spatial frequency components.
The low spatial frequency component of the image being processed is obtained by determining the mean of grey values of pixels present in a bi-dimensional window of appropriate size, whereas the high spatial frequency component is obtained as the difference between the image itself and the low frequency component.
The low frequency component is then altered through a non-linearity which is dependent on the brilliance characteristics of the image.
To modify the high frequency component, that is the contrast signal, and accordingly to regain dim details of the image, a second non-linearity is used where a contrast amplification factor is determined according to the brilliance characteristics of the image being processed. It is mandatory that both non-linearities act to make the contrast enhancement high where the reduction in brilliance variation is large.
In fact, where the image is prevailingly a brilliant one, that is, if a possible saturation toward the white occurs, the reduction in brilliance should be applied by compressing the levels of grey approaching the white, and for given levels, by applying a high contrast amplification to bring to full view details of the image which were only dimly visible.
The reverse holds where the image to be processed is a dark one.
A two-channel filter operated in the manner described above is disclosed, for example, by Tamar Peli and Jae S. Lim in the article, "Adaptative Filtering for Image Enhancement", Optical Engineering, Vol. 21, pages 108-112 (January/February, 1982).
However, the applicability of the above-described two-channel filter to image processing is limited.
In fact, the patterns of the curves which provide the non-linearities for the filter, once they are set for one class of images, e.g. very dark images, cannot effectively be used to process very bright images because no improvement would be obtained on them.